Seismic surveys seek to acquire seismic data that can be used to extract information on the geological features of the subsurface region under investigation. Generally, seismic data provides raw information on geological features that then needs to be processed in order to build a model representing the subsurface region with accuracy.
Special features of the subsurface region can be identified directly on raw seismic data. Such raw seismic data can be browsed through by an operator for example in a 3D representation called seismic cube or seismic image block. Such representations of the seismic data can represent information as a function of time or as a function of depth.
Among the special geological features that can be identified on three-dimensional representations of a subsurface region, geological faults are remarkable insofar as they form interfaces at which strong discontinuities in seismic data lead to an increased complexity of the inverse problem. It is much recommended to identify and characterize these faults prior to any mathematical modeling based on seismic data.
Identifying, locating and mapping faults (i.e. “estimating” faults) from seismic data is not an easy task. Indeed, faults come in different shapes and generally form a whole network of discontinuities in a subsurface region. Faults are not necessarily perpendicular to seismic horizons, and can form a complex network in which several faults intersect.
One prior art method for estimating faults in a three-dimensional seismic image block representation of a subsurface region consists in manually selecting points belonging to a seismic fault in the representation. A manual picking is time consuming because it requires a considerable amount of points to get an accurate and complete two-dimensional estimation of a seismic fault. The required number of points is high even in the case of seismic faults having a substantially planar shape.
Locations of a seismic image block assumed to correspond to faults can also be fitted with a network of planes based on the maximum values of fault attributes in seismic data according to a method called “fault peeling”. This method works well in the case of simple planar-shaped seismic faults. However, more complex shapes require a lot of calculation steps and approximations to generate the network of planes and such a method produces triangulated surfaces that still require further processing to be smoothed.
Another method to estimate seismic faults in a three-dimensional seismic image block representation of a subsurface region consists in animating the three-dimensional representation of the seismic data to help a user visualize the position of seismic faults. This method called “fault tracking” provides an improved manual picking of points on the seismic fault but still requires a lot of manual input and a considerable amount of points to generate a full surface characterization of a seismic fault.
Therefore, a method that requires fewer inputs from an operator to fully characterize a seismic fault and that can provide an accurate picture of a seismic fault is sought.